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Results 11 - 19 of 19 for ranked_type (0.16 sec)
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tensorflow/compiler/mlir/tensorflow/ir/tf_ops_n_z.cc
// Returned attribute has integer elements of the given width. static Attribute ConvertShapeToAttr(Type input_ty, int out_width) { auto ranked_ty = input_ty.dyn_cast<RankedTensorType>(); if (!ranked_ty || !ranked_ty.hasStaticShape()) return {}; auto shape = ranked_ty.getShape(); int rank = shape.size(); SmallVector<APInt, 4> dimensions; dimensions.reserve(rank); for (int i = 0; i < rank; ++i)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 22:07:10 UTC 2024 - 170.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf.cc
// the given type. TensorType UpdateElementTypeTo(Type ty, Type element_ty) { auto ranked_ty = mlir::dyn_cast<RankedTensorType>(ty); if (!ranked_ty) { return UnrankedTensorType::get(element_ty); } return RankedTensorType::get(ranked_ty.getShape(), element_ty, ranked_ty.getEncoding()); } template <typename SrcOpT, typename DstOpT>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 291.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf_with_tf2xla.cc
// dimensions. bool IsBounded(Type ty) { auto ranked_ty = mlir::dyn_cast<RankedTensorType>(ty); if (!ranked_ty) return false; if (ranked_ty.hasStaticShape()) return true; auto encoding = mlir::dyn_cast_or_null<TypeExtensionsAttr>(ranked_ty.getEncoding()); if (!encoding) return false; for (int i = 0; i < ranked_ty.getRank(); ++i) { if (ranked_ty.isDynamicDim(i) &&
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 21:49:50 UTC 2024 - 9.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/tf2xla_rewriter.cc
bool IsBounded(Type ty) { auto ranked_ty = mlir::dyn_cast<RankedTensorType>(ty); if (!ranked_ty) return false; if (ranked_ty.hasStaticShape()) return true; auto encoding = mlir::dyn_cast_or_null<TypeExtensionsAttr>(ranked_ty.getEncoding()); if (!encoding) return false; for (int i = 0; i < ranked_ty.getRank(); ++i) { if (ranked_ty.isDynamicDim(i) &&
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:16:07 UTC 2024 - 18.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/unroll_batch_matmul.cc
} // Combine the result of each individual MatMul into a rank-3 tensor. Type packed_type = RankedTensorType::get( {bcast.output_batch_size(), rows, cols}, element_type); const auto axis = rewriter.getI64IntegerAttr(0); auto pack_op = rewriter.create<TF::PackOp>(loc, packed_type, /*values=*/matmuls, axis); // Reshape the rank-3 tensor into the correct output shape.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 11.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/fallback_to_flex_ops.cc
return f.isExactlyValue(value); }); } // Returns true if the rank of the value equals to the given rank. bool RankEquals(Value value, int rank) { auto rank_type = mlir::dyn_cast<RankedTensorType>(value.getType()); return (rank_type && rank_type.getRank() == rank); } #include "tensorflow/compiler/mlir/lite/quantization/tensorflow/fallback_to_flex_patterns.inc" void FallbackToFlexOps::runOnOperation() {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 12.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v1/compile_mlir_util.cc
// neither. mlir::RankedTensorType GetBufferType(mlir::Type ty) { auto ranked_ty = mlir::dyn_cast_or_null<mlir::RankedTensorType>(ty); if (!ranked_ty) return {}; int64_t rank = ranked_ty.getRank(); llvm::SmallVector<int64_t, 4> dims = llvm::to_vector<4>(ranked_ty.getShape()); auto encoding = mlir::dyn_cast_or_null<mlir::mhlo::TypeExtensionsAttr>( ranked_ty.getEncoding()); if (encoding && !encoding.getBounds().empty()) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 17:24:39 UTC 2024 - 45.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/lower_tf.cc
// to expand at the given `axis`. Type InferExpandDimsType(Type ty, int64_t axis, Builder *builder) { auto ranked_ty = mlir::dyn_cast<RankedTensorType>(ty); // Unranked type. if (!ranked_ty) return ty; auto shape = llvm::to_vector<4>(ranked_ty.getShape()); if (axis < 0) axis += ranked_ty.getRank() + 1; shape.insert(shape.begin() + axis, 1); return tensorflow::GetTypeFromTFTensorShape(shape,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 74.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo.cc
limit = rewriter.getIntegerAttr(element_type, type.getShape()[dimension]); delta = rewriter.getIntegerAttr(element_type, 1); } else { return failure(); } auto range_type = RankedTensorType::get({type.getShape()[dimension]}, element_type); Value start_op = rewriter.create<TF::ConstOp>(iota_op.getLoc(), start);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 154.9K bytes - Viewed (0)